Evolution of HealthCare with Machine Learning

ML can be used to predict the problems of the patient in the early stages of severity itself by learning the patterns from the patient data. We have developed to a point where we are using the machine to do operations on the patient where it turns out to be more precise, accurate, and efficient compared to doctors. There are challenges as well that are to be dealt with prior care while using this method such as datData plays a very important role in analyzing the features of anything. The world is surrounded by numerous data where it is to be analyzed and used in an effective way to satisfy our needs.

So the collection of data and analyzing the patterns in it is very important to predict the behavior of the upcoming data that is to be added by comparing it with the ones we have. Predicting the patterns from big data is indeed a challenge. So here comes an idea how about machines do these predictions that too in less amount of time and with a precise accuracy that is Machine Learning. Machine Learning is a branch of Artificial Intelligence (AI) that has a set of algorithms that identify the patterns among the big data and gives accurate predictions without being programmed to do so. Simply it learns the data and predicts the patterns in the data without being programmed by the user.

The better the algorithm the better is the prediction. One of the most important applications of Machine Learning is using this technology to save lives that is the Healthcare field. a security, System reliability, etc. The world is progressing day by day in this field and we hope to see a greater advancement in our near future.

Machine Learning:

Machine Learning is the field of study that gives computers the capability to learn without being explicitly programmed.

Formal Definition:

A machine is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E.

Types of Machine Learning:

Supervised Learning:

Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input-output pairs.It infers a function from labeled training data consisting of a set of training examples.

Unsupervised Learning:

Unsupervised Learning is a machine learning technique in which the users do not need to supervise the model. Instead, it allows the model to work on its own to discover patterns and information that was previously undetected.

Reinforcement Learning:

Reinforcement learning is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward.

Health Care:

Health care is the maintenance or improvement of health via the prevention, diagnosis, treatment, recovery, or cure of disease, illness, injury, and other physical and mental impairments in people. Health care is delivered by health professionals and allied health fields. Medicine, dentistry, pharmacy, midwifery, nursing, optometry, audiology, psychology, occupational therapy, physical therapy, athletic training and other health professions are all part of health care. It includes work done in providing primary care, secondary care, and tertiary care, as well as in public health.